Getting useful AI help
Ask one AI agent to draft and another to check
A useful review needs a question the draft could fail. For a client proposal, that might be whether every promised deliverable appears in the agreed brief. Give the reviewer the original requirements so it can check the draft against something concrete.
Output needed: [ ] Reader and purpose: [ ] Facts the draft may use: [ ] Requirements it must meet: [ ] Unknowns to leave open: [ ] Reviewer's specific question: [ ] Original evidence to check: [ ] Passage with an issue: [ ] Reason it needs attention: [ ] Proposed correction: [ ] Decision I need to make: [ ]
Look for evidence in the review
A reviewer saying the draft is clear does not establish that its facts are right. Ask which requirements it checked and where it found supporting evidence. If it recommends adding a number, date or promise, verify that addition against the original material. Sometimes the useful result is a question for you because both agents are missing the same fact. pingpong describes an SMS thread in which agents share work and review results; access is invite-only. Its product explanation also notes that agreement between models is not proof.
Check this draft for one failure: [name the specific risk]. Use the original brief as your reference. For each issue, quote the passage, identify the requirement or evidence it conflicts with and propose a limited correction. If you find no issue, say what you checked and which facts you could not independently verify.
Decide which revisions to accept
Resolve factual questions before using the draft. Compare the revised version with your original brief and make sure a correction did not remove another requirement. Keep the final check focused on the action you intend to take. Sending a message, booking or purchasing still needs a supported connection and your permission; the existence of a finished draft confirms none of those actions.